Search Results for author: Feiwen Zhu

Found 3 papers, 0 papers with code

Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data

no code implementations16 Jul 2021 Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei zhang

Reinforcement learning (RL)-based auto-pruning has been further proposed to automate the DNN pruning process to avoid expensive hand-crafted work.

Neural Network Compression reinforcement-learning +1

FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads

no code implementations23 Sep 2020 Zhen Zheng, Pengzhan Zhao, Guoping Long, Feiwen Zhu, Kai Zhu, Wenyi Zhao, Lansong Diao, Jun Yang, Wei. Lin

We show in this work that memory intensive computations can result in severe performance problems due to off-chip memory access and CPU-GPU context switch overheads in a wide range of deep learning models.

Code Generation

Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip

no code implementations ICLR 2018 Feiwen Zhu, Jeff Pool, Michael Andersch, Jeremy Appleyard, Fung Xie

Recurrent Neural Networks (RNNs) are powerful tools for solving sequence-based problems, but their efficacy and execution time are dependent on the size of the network.

speech-recognition Speech Recognition

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